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Originally published In Press as doi:10.1074/jbc.M411727200 on November 15, 2004

J. Biol. Chem., Vol. 280, Issue 6, 4992-5003, February 11, 2005
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Reduced Expression of the Insulin Receptor in Mouse Insulinoma (MIN6) Cells Reveals Multiple Roles of Insulin Signaling in Gene Expression, Proliferation, Insulin Content, and Secretion*{boxs}

Mitsuru Ohsugi, Corentin Cras-Méneur, Yiyong Zhou, Ernesto Bernal-Mizrachi, James D. Johnson, Dan S. Luciani, Kenneth S. Polonsky, and M. Alan Permutt{ddagger}

From the Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, St. Louis, Missouri 63110

Received for publication, October 14, 2004 , and in revised form, November 9, 2004.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 REFERENCES
 
The role of insulin signaling in pancreatic {beta} cells has become increasingly apparent. Stably transformed insulinoma cell lines (MIN6) were created with small interfering RNA resulting in the reduction of insulin receptor (IR) expression up to 80% (insulin receptor knockdown, IRKD{Delta}80). Functionally perturbed IR signaling was confirmed with the absence of insulin-stimulated insulin receptor substrate 1 tyrosine phosphorylation. Additionally, Akt phosphorylation was reduced and responded poorly to glucose stimulation. Gene expression profiling revealed that reduced IR expression was associated with alterations in expression of >1,500 genes with diverse functions. IRKD cells exhibited low rate of proliferation due to delay in transition from G0/G1 to S phase, whereas susceptibility to apoptosis did not differ from that of control cells. Insulin content was reduced in proportion to the reduction of IR. IRKD cells maintained glucose responsiveness as measured by NAD(P)H generation, whereas Ca2+ responses and insulin secretion were enhanced. IRKD{Delta}80 and control cells were treated with glucose (25 mM) or insulin (100 nM) for 45 min, and gene expression profiles were assessed. Transcriptional activation of several hundred early response genes common to both glucose and insulin stimulation was observed in control cells. In IRKD{Delta}80 cells, insulin failed to activate any genes as anticipated. Importantly, glucose stimulation of gene expression in IRKD{Delta}80 cells showed that most genes previously activated by glucose were no longer activated, suggesting a major autocrine/paracrine effect of insulin on glucose-regulated gene expression. On the other hand, there were a number of glucose-regulated genes in the IRKD{Delta}80 cells that were not previously observed in control cells, suggesting a feedback regulation of insulin signaling on glucose-regulated gene expression. These results demonstrate important roles of the insulin receptor in islet {beta} cell gene expression and function and may serve to elucidate molecular defects in animal models with diminished {beta} cell insulin signaling.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 REFERENCES
 
Pancreatic {beta} cells dynamically adapt to their environment (1, 2). Changes in plasma glucose concentration along with various hormones and growth factors have been shown to be major determinants of insulin secretion, biosynthesis, and islet mass (3, 4). The islet {beta} cell responds to these changes in its environment by altering its transcriptional responses, and these changes in gene expression ultimately result in altered mass and function. However, the signaling pathways activated by these environmental changes and the ensuing transcriptional events that mediate these biological responses are only beginning to be elucidated. Specifically, the relationships between the signaling pathways activated by glucose and those activated by growth factors such as insulin remain unclear.

The roles of insulin as a growth factor in the modulation of {beta} cell mass and function have been implied by the results of recent experiments. Glucose stimulation of {beta} cells in culture has been shown to result in the activation of the IR as does the application of exogenous insulin, suggesting that insulin secreted from {beta} cells binds to its receptor eliciting a physiological response (5, 6). There have been many in vivo as well as in vitro studies attempting to clarify the roles of insulin signaling in {beta} cell function; however, no consensus has yet been achieved (reviewed in Ref. 7 and references therein). Some have suggested that insulin inhibits glucose-stimulated insulin secretion (8–11), but others have reported the opposite (12–18). Most recently, Da Silva Xavier et al. (19) reported no glucose-stimulated insulin secretion in the absence of insulin signaling. Furthermore, the potential importance of autocrine/paracrine insulin signaling in pancreatic {beta} cells, especially on {beta} cell mass, was highlighted by the {beta} cell-specific insulin receptor (IR)1 knock-out ({beta}IRKO) mouse model (16) as well as in IR substrate 2 (IRS-2) null mice (11, 20), both of which developed impairment of {beta} cell growth and overt glucose intolerance. However, in the case of the {beta}IRKO mouse model, the conclusion that insulin signaling in the {beta} cell is important for controlling {beta} cell mass is confounded by hypothalamic reduction of the insulin receptor with concomitant tendency to obesity and insulin resistance that may have secondary harmful effects on the {beta} cell. Additionally, Wicksteed et al. (21) recently demonstrated that neither endogenous or exogenous insulin affected insulin secretion, proinsulin translation, preproinsulin mRNA levels, or total protein synthesis in primary cultures of rodent islets for either short (1 h) or long (24 h) incubation. Thus together these studies leave open the question of whether insulin, acting through autocrine/paracrine effects, is a modulator of {beta} cell function and mass.

Because it is difficult to dissect molecular defects in animal models that result in reduction of the small amount of islet tissue, we approached this problem by studying glucose-responsive insulinoma cells in culture. In these studies, we sought to define the roles of insulin signaling through its receptor in {beta} cell and the effects of glucose on these processes. Creation of stable insulinoma cell lines expressing small interfering RNA (siRNA) to reduce the synthesis of the IR allowed us to examine the effects of reduced IR signaling on {beta} cell function. Stable reduction of IR led to alterations in expression of an unexpected number of genes. Additionally, we observed a role of the IR in proliferation, insulin content, glucose-stimulated insulin secretion, and glucose-regulated early gene expression.


   EXPERIMENTAL PROCEDURES
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
RESULTS
 DISCUSSION
 REFERENCES
 
Construction of siRNA Expressing Plasmids—A polIII-mediated small interfering RNA expressing plasmid vector system (pSUPER vector) was constructed according to the methods described by Brummelkamp et al. (22). 64-base DNA oligonucleotides corresponding to sense target sequence, hairpin loop, and antisense target sequence were synthesized (Integrated DNA Technologies, Coraville, IA), annealed together, and then ligated into BglII and HindIII digested pSUPER vector. Plasmids were purified with Wizard Plus Maxipreps kit (Promega, Madison, WI). A target sequence against mouse IR was found, 5'-ACTGCATGGTTGCCCATGA-3', which yielded a satisfactory loss of function. A control oligonucleotide with the same GC content and no corresponding mammalian gene, 5'-GCTACAGTAGACGGAATCG-3', was utilized as a scrambled control.

Cell Culture, Transfection of Insulinoma Cells, and Selection of Stably Transfected Clones—The MIN6 insulinoma cell line was a kind gift of Dr. Jun-ichi Miyazaki (Osaka University, Osaka, Japan). MIN6 cells were maintained in Dulbecco's modified Eagle's medium containing 25 mM glucose supplemented with 15% heat-inactivated fetal bovine serum (FBS), 100 units/ml penicillin, 100 µg/ml streptomycin, 100 µg/ml L-glutamine, and 5 µl/liter {beta}-mercaptoethanol in humidified 5% CO2, 95% air at 37 °C (23). Parental MIN6 cells used for plasmid transfection were between passages 24 and 26. Polyamine transfection reagent TransITTM-LT1 (Mirus Corporation, Madison, WI) was used to transfect the insulinoma cells according to the company's instructions. A total of 10 µg of pSUPER vector and 40 µlof TransIT-LT1 were used for each 10-cm plates. 1 µg of pCDNA 3.1 plasmid, which contains a neomycin cassette, was also transfected to each plate at the same time to facilitate selecting stably transfected cells with G418 (a neomycin derivative). The transfected cells were first selected with culture medium containing 500 µg/ml G418 (Mediatech, Herndon, VA) for 4 weeks, and then isolated colonies of the surviving cells (defined as passage 4) were transferred to a 6-well tissue culture plate and maintained in culture medium with 200 µg/ml G418. Protein levels and mRNA expression were tested at passage 7–8, and clones were further maintained. MIN6 cells transfected with empty pSUPER vector were designated as Con(E), those with scrambled target sequence were referred to as Con(S), and those with reduced IR expression were designated as insulin receptor knockdown (IRKD). Con(E), Con(S), and IRKD cells were propagated by weekly passage and were used for experiments herein between passages 9 and 18, which corresponded to passages 33 and 42 of parental MIN6 cells.

Quantitative RT-PCR (qRT-PCR)—Total RNA was purified, and 1 µg was used to prepare cDNA, primed with random hexamers, and reverse-transcribed with Superscript II (Invitrogen) according to the manufacturer's protocol. qRT-PCR was performed by monitoring in real time the increase in fluorescence of the SYBR Green dye (ABI) as described previously (24, 25) using the ABI 7000 sequence detection system (Applied Biosystems). For comparison of transcript levels between samples, a standard curve of cycle thresholds for serial dilutions of a cDNA sample was established and then used to calculate the relative abundance of each gene. Values were then normalized to the relative amounts of 18 S ribosomal RNA, which were obtained from a similar standard curve. This control was chosen after observing that 18 S rRNA levels correlated well with cyclophilin and tubulin mRNA levels when MIN6 cells were subject to different glucose concentrations for various durations including ones used in these studies. All of the PCR reactions were performed as at least replicates of four. Standard error of the quantity of transcript normalized to the amount of 18 S ribosomal RNA was calculated from a formula with consideration of error propagation. When gene expression levels of two conditions were compared, the ratio was expressed with standard error calculated from the same formula. Specificity of each primer pair was confirmed by melting curve analysis and agarose-gel electrophoresis of PCR products. Sequences of primers used in this study are as follows: insulin receptor, forward 5'-TTTGTCATGGATGGAGGCTA-3' and reverse 5'-CCTCATCTTGGGGTTGAACT-3'; immediate early response 2 (Ier2), forward 5'-CAGCGATTTGAGCGACAGTA-3' and reverse 5'-GGGTCCACAGTTCAGGAGAC-3'; early growth response 1 (Egr1), forward 5'-CGAATCTGCATGCGTAACTT-3' and reverse 5'-GCAAACTTCCTCCCACAAAT-3'; inhibitor of DNA binding 2 (Id2), forward 5'-GGACGACCCGATGAGTCT-3' and reverse 5'-TGCTGGGCACCAGTTCCTT-3'; transducer of ErbB-2.1 (Tob1), forward 5'-GAAGAATAGTGGCCGTAGCA-3' and reverse 5'-TTCAGGAGGTGGTTCACATT-3'; DNA segment, Chr4, Wayne State University 53, forward 5'-TTCGCCTGAGTGAGAAAGAT-3' and reverse 5'-CAAGTCGAAGTTGGCTGTTC-3'; cyclin E1, forward 5'-TCGTTACATGGCATCACAAC-3' and reverse 5'-AAACTGGTGCAACTTTGGAG-3'; Foxo3, forward 5'-ACTCCAAGACCTGCTTGCTT-3' and reverse 5'-GGTGCTAGCCTGAGACATCA-3'; p21CIP1, forward 5'-CCTGACAGATTTCTATCACTCCA-3' and reverse 5'-CAGGCAGCGTATATCAGGAG-3'; and cyclin D2, forward 5'-TTTCCTCTGGCCATGAATTA-3' and reverse 5'-CAGCTTGGAAGCTAGGAACA-3'.

Immunoprecipitation and Western Blotting—Cells were incubated in medium containing 5 mM glucose and 2% FBS for 18 h (defined as "unstimulated" state) followed by treatment of 25 mM glucose or 100 nM insulin for indicated duration of time. Cells were lysed with buffer (PBS, 1% Triton X-100, 1 mM EDTA, 1 mM EGTA, 0.01 M dithiothreitol, 1 mM Na3VO4, and a tablet of Complete protease inhibitor mixture (Roche Applied Science)). For IRS-1 immunoprecipitation, 100 µg of cell lysates were subjected to immunoprecipitation with anti-IRS-1 rabbit polyclonal antibody (BD Transduction Laboratories, San Diego, CA) and immobilized on protein G-Sepharose beads. For Western blotting, total proteins or immunoprecipitates were separated by electrophoresis though 10% polyacrylamide, 0.1% SDS gels and transferred to polyvinylidene difluoride membranes followed by immunoblotting. Immunodetection was performed with Western Lightning (PerkinElmer Life Sciences) following the manufacturer's protocol. Antibodies used in this study were as follows: anti-insulin receptor {beta} subunit (BD Transduction Laboratories); anti-{beta} actin (Sigma); anti-phosphospecific (Ser-473) Akt; anti-Akt; and anti-phosphotyrosine (Cell Signaling, Boston, MA).

Labeling of RNA Transcripts for Microarray, Hybridization, and Data Acquisition—First strand cDNA was generated by oligo(dT)-primed reverse transcription (Superscript II; Invitrogen) utilizing the 3DNA Array 50 kit (Genisphere) (26). Modified oligo(dT) primers were utilized in which a fluorophore/dendrimer-specific oligonucleotide sequence was attached to the 5' end of the dT primer. Two hybridizations were carried out in a sequential manner. The primary hybridization was performed by adding 38 µl of sample to the microarray under a supported glass coverslip (Erie Scientific) at 50 °C for 16–20 h at high humidity in the dark. Secondary hybridizations were carried out using the complimentary capture reagents provided in the 3DNA Array 50 kit. Slides were scanned on a PerkinElmer ScanArray Express HT scanner to detect Cy3 and Cy5 fluorescence. Laser power was kept constant for Cy3/Cy5 scans, and photomultiplier tube was varied for each experiment based on background fluorescence. Gridding and analysis of images were performed using QuantArray (PerkinElmer Life Sciences). Each spot was defined on a pixel-by-pixel basis using a modified Mann-Whitney statistical test.

Microarray Sample Pairing—To assess gene expression alteration by comparing two conditions, transcripts from each sample were directly compared using EPCon-pancreatic cDNA microarray with ~11,000 probes (27). For each sample pair, transcripts from one condition were labeled with either Cy3 or Cy5 and hybridized with the Cy5- or Cy3-labeled transcripts from the partner condition. Another pair of RNAs was also labeled-inverting dyes. Those pairs of hybridization were repeated twice. When unstimulated MIN6-Con and IRKD{Delta}80 cells were compared, four microarrays were used. For assessing transcriptional responses either to glucose or insulin treatment, a total of eight microarrays per cell line were used.

Microarray Normalization and Statistical Analysis—In the microarray studies performed herein, normalization and statistical analyses were performed as follows. Only probes with a signal intensity of 2.0-fold or greater above the corresponding background intensity in both channels were chosen for calculation of fold changes. The intensity of each spot was adjusted by subtracting background intensities. The log ratio of Cy5 and Cy3 channel intensity of each spot was then calculated, and the median of the log ratio from all of the probes was subtracted from each log ratio (28).

The log ratios from four pairs of "dye flip" hybridizations were utilized to estimate probe-specific measurement variation (29). Probe-specific measurement variation was subtracted from log fold change to calculate the final normalized log fold change (probe-specific normalization).

From the pairing scheme, four direct ratios were obtained for each comparison. These ratios were used to calculate the average fold change as well as the mean ± S.E. 95% confidence intervals (CI, two standard errors away from the average fold change) were calculated with attention to the change of distribution when converting log fold change to fold change (30). Criteria were set to assess changes in gene expression that included a fold change of 1.35 or more compared with "unstimulated." This criterion was selected after observing that the mean variance of all of the probes was 0.15, and the false positive rate was estimated to be 0.0032%. With similar multiple hybridizations and cDNA microarrays, the fold change of 1.3–1.4 was utilized to identify significant gene expression change in other studies (31–33). Additionally, significant fold changes required that the 95% CI of the fold change, two standard errors away from the fold change, excluded 1. Thus any fold changes meeting these criteria could be considered significant with a p value of <0.05.

Microarray Annotation and Gene Ontology Functions—Annotation for the clones on the arrays were performed as reported previously using BLASTn analysis against the public databases (34, 35). Gene ontology functions were gathered through the Source Repository (source.stanford.edu/) (36) and classified according to the categories provided by the Gene Ontology Consortium (www.geneontology.org/) (37).

Hierarchical Clustering—Hierarchical clusters were performed using the Genesis software version 1.3 (Institute for Biomedical Engineering, Graz University of Technology, Graz, Austria) (38). Heat maps generated by hierarchical clustering were created using the average linkage clustering (Euclidean distances) directly from the logarithmic ratios (base e), and the intensity of those colors indicates the degree of fold changes in natural log scale (above 1.5 or below -1.5 fold changes are saturated).

BrdUrd Incorporation—Two days before the procedure, cells were seeded onto 25-mm glass coverslips at a density of 2 x 106 cells/ml. Medium was changed once 24 h before the procedure, and then during the last hour of culturing, BrdUrd (10 µM) was added to the medium. Detection of BrdUrd was carried out with immunohistochemistry utilizing anti-BrdUrd monoclonal antibody according to the manufacturer's recommendations (Roche Diagnostics, Indianapolis, IN). Cells were stained with 1 µg/ml 4',6-diamidino-2-phenylindole for identifying nucleus. At least four different fields from each coverslip were selected to count at least 2,000 cells to calculate the rate of BrdUrd-positive cells. Shown are the results from six independent samples from each of the cell lines.

Cell Cycle Analysis with Flow Cytometry—Cells were lifted off the plates with trypsin-EDTA and were resuspended in PBS containing 1% FBS and then fixed with 70% ethanol. Cells were resuspended again in PBS containing 30 µg/ml propidium iodine and 250 mg/ml RNase A and further incubated at 4 °C for 1 h before analysis with a FACSCalibur laser-based flow cytometer (BD Biosciences). The cell cycle phase distribution was analyzed with FLOWJO software (Tree Star, Ashland, OR).

Apoptosis Assays—The terminal deoxynucleotidyltransferase-mediated dUTP nick end labeling (TUNEL) technique was used to detect DNA strand breaks formed during apoptosis (39). Cells on coverslips were fixed with 4% paraformaldehyde for 45min at room temperature and then permeabilized with 1% Triton X-100. After a rinse with PBS, cells were incubated with fluorescein isothiocyanate (FITC)-labeled dUTP in the presence of enzyme terminal deoxynucleotidyltransferase for 1 h at 37 °C. Coverslips were mounted on glass slides in mounting medium containing the counterstain propidium iodide (2.5 µg/ml) and visualized using a fluorescent microscope. At least 500 cells/field were scored in a blinded fashion to determine the percentage of TUNEL-positive cells. Four fields per slide were used, and six independent slides were used for the final result. For annexin V assay (40), the cells were lifted off the plate using trypsin-EDTA. After washing, the cells were incubated with a label containing annexin V linked to FITC. FITC-positive cells/propidium iodide cells were analyzed by flow cytometry.

Insulin Secretion—Cells (5 x 105 cells/well, 24-well plate) were seeded and cultured regularly for 2 days. The cells were preincubated for 30 min in HEPES-balanced Krebs-Ringer bicarbonate buffer (119 mM NaCl, 4.74 mM KCl, 2.54 mM CaCl2, 1.19 mM MgCl2, 1.19 mM KH2PO4, 25 mM NaHCO3, and 10 mM HEPES, pH 7.4) containing 0.5% BSA with 5 mM glucose and then incubated for 2 h with various concentrations of glucose or KCl. Released insulin was measured by radioimmunoassay using rat insulin as standard. The cellular protein content or DNA content was also used to normalize the amount of insulin secretion.

Measurement of Insulin Content—Cells (5 x 105 cells/well, 24-well plate) were seeded and grown overnight. The medium was removed, and the cells were washed twice with ice-cold PBS and extracted with acid ethanol (15 mM/liter HCl, 75% ethanol) for 18 h at 4 °C. After clarification of the extracts by centrifugation at 15,000 x g at 4 °C, the insulin concentration was measured by radioimmunoassay with rat insulin as a standard.

Measurement of NAD(P)H Production—NAD(P)H autofluorescence was measured essentially as described previously (41, 42). Cells plated on coverslips were transferred to a temperature-controlled chamber on an inverted microscope with a x40 objective (Eclipse TE300, Nikon Inc.). Cells were perifused continuously at 2.5 ml/min with Ringer's solution containing 144 mM NaCl, 5.5 mM KCl, 1 mM MgCl2, 2 mM CaCl2, 20 mM Hepes (adjusted to pH 7.35 by NaOH), and glucose as indicated. Prior to image acquisition, the cells were equilibrated for 30 min in buffer containing 3 mM glucose. For NAD(P)H autofluorescence measurements, cells were excited at 365 nm and fluorescent emission was filtered using a 4',6-diamidino-2-phenylindole/FITC/Texas Red polychroic beamsplitter and triple band emission filter (Chroma Technology). Images were collected at 5-s intervals with a CoolSNAP HQ camera (Roper Scientific) controlled using Metafluor software (Universal Imaging Corp.). NAD(P)H recordings were corrected for the downward trend due to photobleaching. The trend was projected by an exponential fit to prestimulus and poststimulus recordings of 10-min duration, and the time series was subsequently divided by the estimated trend function, thus expressing NAD(P)H changes relative to base-line autofluorescence. MIN6 cell-metabolic responses were quantified by the "area under the curve" of the detrended NAD(P)H profiles from the time of glucose rise to 5 min after returning to basal glucose. Area under the curve calculations were done using trapezoidal integration in the Igor Pro Software (Wavemetrics, Inc.).

Measurement of Intracellular [Ca2+]—Calcium imaging was performed essentially as described (43). Cells were plated on glass coverslips at the density of 1 x 106 cells/ml. Cells were incubated with 1 mM Fura-4F/AM (Molecular Probes) in Krebs-Ringer's solution for 30 min and rinsed in Ringer's solution for an additional 30 min. Coverslips in a narrow 32 °C chamber were continuously perfused with preheated solutions to maximize control over the contents of the bath. Recordings were made by using a monochromator for excitation, a CCD camera (TILL Photonics, Gräfelfing, Germany), and an IX70 microscope (x20 objective; Olympus, Tokyo, Japan). Ratios (340/380) were calibrated by exposing cells to 10 µM ionomycin. Calcium responses were defined as having 1-min bins with a mean [Ca2+]c that was more than two standard deviations over the mean [Ca2+]c of the 5-min pretreatment period. The amplitude and rate parameters of the Ca2+ signals were calculated as described previously (44).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
DISCUSSION
 REFERENCES
 
Reduced IR Expression by siRNA—After clones of MIN6 cells stably transfected with the siRNA-expressing vector were isolated, reduced IR expression was confirmed. As shown in Fig. 1A, quantitative RT-PCR of RNA extracted from these siRNA cell lines established significantly diminished mRNA expression of the IR in IRKD cells. The maximal effect of siRNA was observed in one cell line with the reduction of IR mRNA by 80% (IRKD{Delta}80). Various degrees of mRNA reduction between 20 and 80% (Fig. 1A, IRKD{Delta}20, IRKD{Delta}50, and IRKD{Delta}80, respectively) were observed, whereas individual cell lines had their stable levels of reduced mRNA on at least three separate occasions throughout the experimental period during which the following experiments were carried out (data not shown). The IR protein expression levels were also reduced as shown in Fig. 1B, and the levels in each cell line corresponded with their respective IR mRNA concentrations. The IR protein levels were also stable throughout the experimental period (data not shown). Two types of control cells were created: 1) Con(E) cells with empty vector to rule out nonspecific effects resulting from plasmid transfection and 2) Con(S) cells expressing a scrambled target sequence to exclude spurious effects of siRNA. As shown in Fig. 1, the IR mRNA as well as protein expression were identical in Con(S) and Con(E) cells. Three Con(E) and two Con(S) cell lines with identical IR expression (data not shown) were used for the following experiments.



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  		FIG. 1.
IR expression in Con(E), Con(S), and IRKD cells. A, IR mRNA expression in control cells, Con(S) and Con(E), and IRKD cells. Measurement of IR mRNA was carried out by qRT-PCR analysis. IR mRNA quantity was first normalized to that of endogenous control 18 S ribosomal RNA. These results were then expressed relative to those in Con(E) cells. IRKD{Delta}80, IRKD{Delta}50, and IRKD{Delta}20 refer to the relative reduction of IR mRNA. The results shown here are representations of three independent measurements mean ± S.E. B, diminished IR protein expression in IRKD cells. Western blot analysis of IR protein in Con(S), Con(E), and IRKD cells was performed with whole cell lysates. IR protein was assessed by using antibody specific for the IR {beta} subunit, and then {beta} actin was used as loading control. The results are representative of three independent measurements. IB, immunoblotting.

 
Perturbed Insulin Signaling as a Result of Reduced IR Expression—The effects of reduced IR expression were first tested by measuring tyrosine phosphorylation of the IR substrate IRS-1 (Fig. 2A). In this experiment, control and IRKD{Delta}80 cells with the least expression of IR among IRKD cells were treated with insulin (100 nM) for 10 min. Both Con(S) and Con(E) cells exhibited robust tyrosine phosphorylation of IRS-1 in response to insulin, whereas IRKD{Delta}80 cells failed to phosphorylate IRS-1 tyrosine residues. Insulin was used as a stimulus to determine the effects of the reduced IR expression in IRKD cells. Insulin signaling was first assessed by measuring tyrosine phosphorylation of the IR substrate IRS-1 (Fig. 2A). In this experiment, control and IRKD{Delta}80 cells with the least expression of IR among IRKD cells were treated with insulin (100 nM) for 10 min. Both Con(S) and Con(E) cells exhibited robust tyrosine phosphorylation of IRS-1 in response to insulin, whereas IRKD{Delta}80 cells failed to phosphorylate IRS-1 tyrosine residues. Thus these results support the conclusion that insulin signaling is diminished in IRKD cells.



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  		FIG. 2.
Perturbed insulin signaling in IRKD cells. A, perturbed IRS-1 tyrosine phosphorylation by insulin in IRKD{Delta}80 cells. Cells were treated with 100 nM insulin for 10 min, and then protein was obtained before and after the treatment. 100 µg of whole cell lysates were immunoprecipitated (IP) with an antibody specific for IRS-1, and then tyrosine phosphorylation was measured with Western blot (IB) analysis using an antibody for phosphorylated tyrosine ({alpha}PY). The membrane was re-used for detecting IRS-1 protein. This blot is representative of two independent experiments. B, differential phosphorylation of Akt1 by glucose in MIN6-Con and IRKD{Delta}80 cells. Cells were pretreated by incubation in 5 mM glucose as described under "Experimental Procedures" and stimulated with 25 mM glucose, and protein was obtained before the treatment and 15 and 45 min after the treatment. Serine 473 phosphorylation was analyzed by Western blot, and then total Akt1 levels were measured. C, densitometric analysis from the data obtained in panel B (n = 3). D, ERK1 and 2 phosphorylation in Con(S) and IRKD{Delta}80 cells after glucose stimulation. This is a representative result of three independent experiments.

 
The effects of glucose on elements of insulin signaling with reduction of IR were tested next. Previous studies had revealed conflicting results regarding the requirement of insulin signaling through its receptor on PI3-kinases and their downstream elements including Akt (5, 19, 21). We had previously observed that glucose treatment resulted in the activation of Akt measured via phosphorylation of Ser-473 with primary cultures of mouse islets as well as in MIN6 cells and that this phosphorylation was PI3-kinase-dependent (45). As shown in Fig. 2B and the densitometric analysis of these data in Fig. 2C, IRKD{Delta}80 cells exhibited a reduction in Akt phosphorylation in the unstimulated state as well as diminished response to glucose stimulation relative to that in Con(E) and Con(S) cells. Thus these results are consistent with the interpretation that glucose activation of Akt phosphorylation in this model is contingent on intact IR/insulin signaling.

Evidence that glucose can activate Erk1/2 independent of insulin secretion was presented by Wicksteed et al. (21). We observed that glucose treatment resulted in robust phosphorylation of Erk1/2 in IRKD cells equal to that in control cells (Fig. 2D), thus demonstrating that at least one glucose effect is direct on some elements of insulin signaling independent of insulin secretion.

Differences of Gene Expression between IRKD{Delta}80 and Con(E) Cells—To further explore the consequences of reduced IR expression, differences in gene expression between the two cell lines were examined under unstimulated conditions. Following an 18-h incubation in medium containing 5 mM glucose and 2% FBS, transcripts from Con(E) and IRKD{Delta}80 cells were compared. There were >1,500 clones of genes that were differentially expressed defined by 1.35-fold with 95% confidence interval excluding 1.0 (n = 4 for each ratio) between the two cell lines (see Supplemental Table 1S). Selected gene ontology function categories are represented in Table I. Knowing that glucose and insulin affect {beta} cell mass, selected genes from the "cell cycle" gene ontology function category are shown. Several genes known to affect {beta} cell proliferation and/or differentiation such as Ipf1 (Pdx1), Pax6, Nkx2.2, Kit, and Isl1 were observed along with transcriptional alterations of numerous genes with diverse functions. These differences could perhaps account for other phenotypic differences previously observed in mouse models following the reduction of insulin signaling in {beta} cells, including changes in insulin synthesis, secretion, proliferation, and apoptosis.


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  		TABLE I
Selected cell cycle-related genes differentially regulated in the IRKD{Delta}80 cells Genes are shown according to their gene ontology functions. Fold changes and 95% CI are shown.

 
Apoptosis and Proliferation in IRKD Cells—Knowing that insulin signaling through PI3-kinase/Akt activates a survival pathway in certain cells (46), we next examined whether perturbed insulin signaling in IRKD cells results in increased apoptosis. First, when the apoptotic rates were assessed for cells using the TUNEL assay, Con(E) cells (3.6 ± 0.2%; n = 6 samples analyzed) and IRKD80 cells (3.4 ± 0.4%; n = 6) had similar TUNEL-positive rates. This result was confirmed with an annexin V assay (Con(E) cells 4.1 ± 0.2%; n = 6 and Con(S) cells 3.4 ± 0.8%; n = 6 versus IRKD80 cells 4.0 ± 0.5%; n = 6). The reduction of glucose (from 25 to 5 mM) and serum (from 15 to 2%) concentrations for 24 h modestly increased the rates of apoptosis measured by annexin V assay, yet the rates did not differ between control cells (Con(E) 5.6 ± 0.8%; n = 6 and Con(S) 6.2 ± 1.0%; n = 6) and IRKD{Delta}80 cells (6.0 ± 1.1%; n = 6).

The proliferation rate assessed by the rate of BrdUrd incorporation per 4',6-diamidino-2-phenylindole-positive cells showed that the number of BrdUrd-positive cells was less for IRKD80 cells (14.6 ± 0.4%; n = 6) compared with Con(E) cells (18.6 ± 1.0%, p = 0.008; n = 6). When three Con(E) cell lines, two Con(S) cell lines, and three IRKD cell lines were compared, flow-cytometric analysis to assess the cell cycle also confirmed that fewer IRKD cells were in S phase compared with control cells (Table II). A total of five control cell lines had identical distributions of cell cycle (data not shown). An analysis of individual IRKD cell lines revealed that IRKD{Delta}80 and IRKD{Delta}50 cells had significantly fewer cells in S phase than did control cells. These results indicated that reduced IR expression in these IRKD cell lines was associated with a small but significant reduction in the number of cells transitioning from G1/G0 to the S phase of the cell cycle.


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  		TABLE II
Cell cycle analysis in IRKD cells Results shown here are cell cycle analyses of combined results of three different MIN6-Con and three IRKD cell lines as well as the analysis of individual IRKD cell lines. Cell cycle distributions of MIN6-Con cell lines were identical (data not shown). n designates total number of samples from two experiments. Asterisk signifies p value <0.05 when compared to MIN6-Con cells.

 
Glucose-stimulated Insulin Secretion and Insulin Content of IRKD Cells—To examine the pattern and threshold of glucose-stimulated insulin secretion, static incubation of cells was performed. Although insulin secretion was comparable at low glucose concentrations (0–5 mM glucose), IRKD cells appeared to secrete more insulin in response to 10, 15, and 25 mM glucose compared with Con(E) and Con(S) cells (Fig. 3A). Furthermore, when treated with 30 mM KCl, insulin secretion from control and IRKD cells did not differ.



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  		FIG. 3.
Insulin secretion, content, mRNA expression, and NAD(P)H production in IRKD cells. A, insulin secretion in IRKD cells. Insulin secretion was tested by static incubation of media containing glucose or KCl for 2 h at the concentrations shown in the figure. Insulin in supernatants was measured with radioimmunoassay, and the results shown here were normalized to total protein content. When normalized to DNA content, the results were identical (data not shown). This is a combined dataset from three independent experiments testing three different MIN6-Con lines as well as IRKD (IRKD{Delta}80, IRKD{Delta}50, and IRKD{Delta}20). Each value indicates per hour insulin secretion with the mean ± S.E. B, insulin content in IRKD cells. Insulin levels were measured with radioimmunoassay, and the insulin content results were expressed/1 x 105 cells. When expressed as insulin content normalized to DNA content, the relative reductions of insulin content in IRKD cells were similar (data not shown). The data were presented as mean ± S.E. C, fractional insulin secretion in IRKD. Insulin secretion in response to glucose or KCl was adjusted relative to insulin content. D, insulin mRNA expression in MIN6-Con and IRKD cells. Measurement of insulin mRNA was carried out by qRT-PCR analysis. Insulin mRNA quantity was first normalized to that of endogenous control 18 S ribosomal RNA. These results were then expressed relative to that in MIN6-Con cells. The data are expressed as the mean ± S.E. of three independent measurements. E, NAD(P)H production in IRKD{Delta}80 cells. NAD(P)H autofluorescence was measured from perifused MIN6-Con and IRKD{Delta}80 cells. The area under the curve of increment NAD(P)H autofluorescence over a 20-min treatment of 10, 20, and 30 mM glucose is described here (see "Experimental Procedures") (n = 13, 13, and 11 samples were tested for 10, 20, and 30 mM glucose, respectively, for MIN6-Con cells. n = 12, 11, and 9 for 10, 20, and 30 mM glucose, respectively, for IRKD{Delta}80 cells).

 
Insulin content of control and IRKD cells were measured to assess the contribution of content to secretion. As shown in Fig. 3B, insulin content in IRKD cells was reduced relative to that in control cells. The decline appeared to be proportional to the reduction of IR expression. This result indicated that enhanced secretion was not due to increased content. In fact, when corrected for content, the fractional secretory rate was markedly enhanced in IRKD cells (Fig. 3C). This reduced insulin content was accompanied by a reduction of insulin mRNA revealed by qRT-PCR of RNA from IRKD cells (Fig. 3D).

NAD(P)H production, which reflects glucose oxidation and mitochondrial function in pancreatic {beta} cells and glucose-responsive insulinoma cells (47, 48), was measured in response to glucose stimulation in Con(E) and IRKD{Delta}80 cells. As shown in Fig. 3E, step increases of glucose from 3 to 10 mM or 20 or 30 mM increased relative NAD(P)H production to a similar extent. This indicated that glucose oxidation through glycolytic pathways and mitochondrial function was not altered in IRKD cells.

We next evaluated glucose-induced [Ca2+]i responses. In the Con(E) cells, the base-line [Ca2+] levels varied between 100 and 300 nM and only a fraction of cells responded to glucose stimulation (Fig. 4A). In contrast, IRKD{Delta}80 cells had lower basal [Ca2+]i at 3 mM glucose (compare Fig. 4, A and B, 101 ± 7 versus 238 ± 13 nM for control cells). When challenged with a stepwise increase to 20 mM glucose, a greater percentage of IRKD cells responded (Fig. 4C) and the fold Ca2+ increase over base line was significantly greater in IRKD{Delta}80 cells (Fig. 4D). When Ca2+ channels were directly opened by depolarizing the cells with 30 mM KCl, no difference was seen between the cell lines (compare Fig. 4, A and B).



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  		FIG. 4.
Intracellular Ca2+ in response to glucose and KCl in MIN6-Con cells (A) and IRKD{Delta}80 cells (B) is shown. Representative tracings of intracellular Ca2+ measurement using Fura-4 are shown. Average Ca2+ concentrations when cells were subjected with perifusates with 3 mM glucose were 238 ± 13 nM in MIN6-Con cells and 101 ± 7 nM in IRKD{Delta}80 cells. C, percentage of cells responding to 20 mM glucose (determined as maximum Ca2+ during glucose treatment above two standard deviations from the base-line Ca2+ concentrations). D, ratios of maximal Ca2+ concentrations during 20 mM glucose or 30 mM KCl treatment to baseline Ca2+ concentrations in responding cells are shown with mean ± S.E. There was a statistical difference in fold Ca2+ increases in response to glucose between MIN6-Con and IRKD{Delta}80 cells (*, p < 0.01) but no difference between the two cell lines after KCl treatment.

 
Altered Glucose-regulated Gene Expression in IRKD Cells— Previous studies have shown that glucose acutely alters early gene expression in islet {beta} cells and that these effects are mediated through depolarization, influx of extracellular Ca2+, and activation of kinase cascades that result in transcriptional activation (49, 50). To examine the role of glucose-stimulated insulin secretion in this process, glucose-regulated early gene expression was examined in IRKD cells. Following glucose and serum starvation for 18 h, cells were treated with 25 mM glucose or 100 nM insulin and RNA samples were extracted at zero time (unstimulated) and after 45 min (stimulated). Stimulated and unstimulated RNAs were hybridized together, and gene expression profiles were assessed with pancreas-specific EPCon cDNA microarrays containing 11,000 probes. To assess the differences in gene expression, hierarchical clustering analysis of all of the genes significantly activated in at least one condition is shown in Fig. 5. This method illustrates in a color scale the global degrees of similarity of fold activation or repression of the same genes by two stimuli. As shown in Fig. 5A, in MIN6-Con cells, there was a remarkable degree of similarity between genes activated or repressed by glucose and insulin. Of 195 clones that appeared to be regulated by glucose, 126 were also regulated by insulin.



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  		FIG. 5.
Hierarchical clustering analysis of gene regulation by glucose or insulin in MIN6-Con and IRKD{Delta}80 cells. Each row in this analysis corresponds to a single gene, and columns are according to treatment. Up-regulated genes are expressed in red, down-regulated genes are in green, and intensity of those colors indicates the degree of fold changes in natural log scale (above 1.5 or below -1.5-fold changes are saturated). A, the ratio of stimulated to unstimulated values for each gene following glucose or insulin treatment in MIN6-Con cells. B, glucose-regulated and insulin-regulated genes in IRKD{Delta}80 cells. C, glucose-regulated genes in MIN6-Con and IRKD{Delta}80 cells.

 
Shown in Fig. 5B are the genes regulated by glucose and insulin in IRKD{Delta}80 cells. Not unexpectedly, however, there were virtually no genes activated by insulin in these cells. Surprisingly, there appeared to be a large number of genes activated by glucose in the IRKD{Delta}80 cells. A side-by-side comparison of the glucose-activated genes in the MIN6-Con versus the IRKD{Delta}80 cells revealed several interesting results (Fig. 5C). For instance, 112 of 125 genes regulated in MIN6-Con cells were no longer activated by glucose in IRKD{Delta}80 cells, suggesting that the majority of glucose-regulated gene expression was mediated through the autocrine/paracrine effect of insulin acting through its receptor. The comparison of glucose-regulated genes between the two cell lines also highlighted the following. 1) The large number of genes was regulated by glucose in IRKD{Delta}80 cells compared with MIN6-Con cells (825 versus 135, respectively). 2) For the most part, the glucose-regulated genes were vastly different between the two cell lines. The results of selected genes were confirmed by qRT-PCR analysis as shown in Table III.


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  		TABLE III
Microarray results validation by quantitative RT-PCR Fold changes observed by microarray or quantitative RT-PCR are shown with 95% CI in parentheses. N.D. denotes the fold change not observed in microarray for technical reasons. Id2 had two microarray probes corresponding to different portion of Id2 cDNA.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
REFERENCES
 
In this study, the reduction of IR expression in insulinoma cells was associated with a surprising number of changes in gene expression and function. These included effects on proliferation, insulin content, glucose-stimulated insulin secretion, and glucose-activated early gene expression. These results may shed some light on the molecular aberrations following reduction of insulin signaling in animal models that result in decreased islet {beta} cell mass and glucose intolerance and in human diabetes as well.

Although the use of loss of function experiment through the use of siRNA has gained widespread acceptance, one must cautiously use appropriate control to guard against nonspecific effects of siRNA (51). For example, although mismatched or scrambled siRNAs were often used as a control, they may be of limited value. However, as demonstrated in this study, this concern is negated by demonstrating the lack of effect of the scrambled oligonucleotides to gene expression (see Fig. 1). Additionally, the mechanisms of a loss of function with these types of experiments can be diverse; therefore, it is important to demonstrate the loss of function at the mRNA as well as protein and functional levels. These were all demonstrated in the current experiments (see Figs. 1 and 2). The ultimate control would be a rescue experiment in which the expression of the insulin receptor cDNA would be mutated at the silent position of the codon and thus not inhibitable by siRNA. In the case of insulin receptor, this is particularly difficult because of the relatively large size of cDNA (>4 kb). Nevertheless, the loss of expression of insulin receptor mRNA, protein, and biological functions and the absence of nonspecific changes in the cells created with scrambled siRNA address the validity of the current observations.

Gene expression profiling revealed that reducing IR expression results in alterations of unexpected numbers of genes. These changes were associated with phenotypic changes noted above, whereas the links between gene expression changes and altered phenotypes are unclear at present. However, it is interesting to speculate that changes in expression of genes with well documented roles in {beta} cell function and survival (52) may participate in creating the altered phenotypes. For example, the expression of Ipf1 (Pdx1), Isl1, Pax6, and Nkx2.2 were each up-regulated in IRKD cells (Table I) and could represent a more differentiated phenotype in the IRKD cells with reduced proliferation. A number of kinases including kit oncogene (53) were also observed to be differentially expressed in IRKD cells. The reduction of the IR was also associated with altered expression of cell cycle-related genes including cyclins D2 and G2, p21CIP, p18, Ches1, and Cdc5l.

Insulin signaling has been shown to be associated with enhanced proliferation and reduced apoptosis in insulin target tissues (46). The reduction of {beta} cell mass and subsequent glucose intolerance of the {beta}IRKO mouse has been suggested to be attributed to either decreased proliferation and/or increased apoptosis (17, 18). No differences in apoptosis, measured by two different methods and tested under unstimulated and nutrientdeprived conditions, were detected in IRKD cells. Significant reduction in proliferation measured by BrdUrd incorporation and by cell cycle analysis was found, and this was associated with reduced phosphorylated Akt1 in IRKD cells. The observation that reduced insulin signaling in the IRKD cells relative to that in MIN6-Con cells was associated with delay in transition from G0/G1 to S phase suggests that insulin signaling in the {beta} cell may contribute to the maintenance of {beta} cell mass through regulation of entry into the cell cycle. However, an important caveat is that the current studies apply only to insulin signaling in insulinoma cells and thus the relevance of these observations to physiology are still speculative at present.

The reduction of insulin content observed in the IRKD cells appeared to be proportional to the reduction in IR expression (Fig. 3B) and was associated with significant reduction in insulin mRNA. This was observed under standard conditions (25 mM glucose), indicating that under these circumstances, the total amount of preproinsulin mRNA differed. As expected after a short glucose stimulus, there was no change in insulin mRNA following 45 min of stimulation in the microarray experiments. Insulin content is a reflection of the balance between preproinsulin mRNA levels (contributed to by changes in insulin gene transcription and preproinsulin mRNA stability) and the rate of proinsulin synthesis at the translational level relative to the insulin secretion rate and intracellular degradation (54). The contributions of these various parameters to the observed decrease in insulin content have not been assessed in the IRKD cells. The decreased content in IRKD is consistent with recent studies describing a positive effect of insulin signaling on insulin synthesis. For example the {beta}IRKO and IRS-2-/- mouse models developed diminished islet insulin content (11, 16, 18, 20). Similarly, PI3-kinase regulatory subunit-deficient mouse islets also exhibited diminished insulin content (10). Several studies of insulinoma cells as well as primary islet cultures reported that insulin content was positively regulated by insulin signaling (6, 43, 55–58). For example, overexpression of IR in insulinoma cells resulted in increased insulin content (6). Thus our findings of reduction in insulin content in proportion to reduction in IR expression in the IRKD cell lines are consistent with the concept that insulin signaling in the {beta} cell is a positive modulator of insulin biosynthesis.

There have been numerous studies suggesting that insulin has either a positive or negative effect on glucose-stimulated insulin secretion (8–19, 21, 43, 59). A recent report by Da Silva Xavier et al. (19), for example, in which transiently exposing MIN6 cells for 24–48 h to siRNA oligonucleotides targeted the IR, demonstrated that glucose-induced insulin release was obliterated in cells with IR knockdown. However, the results of this study showed rather that reduced IR expression enhanced glucose-stimulated insulin release, consistent with a negative feedback of insulin signaling. The difference between the current study and the study by Da Silva Xavier et al. (19) may be in the long term versus short term reduction of IR expression. The enhanced glucose effects in this study did not appear to be due to differences in glucose-metabolic rates as judged by the absence of difference in NAD(P)H production between MIN6-Con and IRKD{Delta}80 cells (Fig. 3E). Intracellular Ca2+ in the IRKD{Delta}80 cells, however, showed enhanced responsiveness to glucose (Fig. 4).

The differences in [Ca2+]i between control and IRKD cells are seen in basal [Ca2+]i levels, proportions of cells responding to glucose, and fold increase in [Ca2+] levels (Fig. 4, A–D). Base-line [Ca2+]i in Con(E) cells are higher and more variable. This could be explained by heterogeneity of Con(E) cells; however, it is unlikely because Con(E) cells were clonally isolated cell lines. It is possible that insulin is not able to exert its inhibitory effect to neighboring cells in IRKD cells, thus leading to more homogeneous base-line [Ca2+]i (Fig. 4B) and to more proportions of cells responding to glucose (Fig. 4C). Enhanced fold increase in [Ca2+]i in IRKD cells was associated with low base-line [Ca2+]i. In some models, insulin signaling has been shown to open KATP channels (60). Thus IRKD cells with reduced insulin signaling might be expected to have more closed KATP channels and Ca2+ influx and insulin secretion. Studies are underway to assess KATP channel activity in IRKD cells, and these may provide further insight into molecular mechanisms for the enhanced effects of glucose on insulin secretion in the IRKD cells. The roles of insulin signaling in glucose-stimulated gene expression in {beta} cells have not been extensively studied. By employing gene expression profiling with endocrine pancreas cDNAs microarrays, we noted that glucose and insulin regulated the transcription of a common set of genes in MIN6 cells within 45 min (Fig. 5A) (61). When glucose-regulated genes in IRKD{Delta}80 cells were analyzed, 112 of 125 genes previously activated in MIN6-Con cells were no longer activated by glucose. This finding indicated that the overwhelming majority of glucose-regulated genes require insulin signaling through its receptor, thus strongly supporting a hypothesis of an autocrine/paracrine effect on gene expression. Assessing the limited number of genes with transient inhibition of insulin signaling, Da Silva Xavier et al. (19) came to the same conclusion. Another finding of the current study was that functional ablation of the IR in IRKD cells led to marked alteration of glucose-regulated gene expression. Many of the genes that were not regulated at all by glucose in MIN6-Con cells then appeared to be regulated in IRKD{Delta}80 cells (Fig. 5C) so that the total number of glucose-regulated genes, both up and down-regulated, was markedly increased in the IRKD{Delta}80 cells. Although the microarray experiments were performed using the Con(E) and not the Con(S) cells, considering the identical phenotypic characteristics of the two cells lines (see Figs. 1, 2, 3 and Table II), microarray experiments were only performed on Con(E) cells. These results indicate that in addition to mediating glucose-stimulated gene expression, insulin signaling is modulating, either in an enhancing or a suppressing manner, glucose-stimulated signaling pathways leading to gene expression. Additionally, it would be desirable to repeat these experiments in primary cultures of islets. Whereas early response genes have been extensively evaluated in response to glucose in primary cultures (49), gene expression profiles need to be repeated in primary cultures of islets from {beta}IRKO animals (62).

The results of these studies where IRKD cells have enhanced glucose-stimulated insulin secretion and enhanced glucose activation of insulin-independent gene transcription are consistent with a testable model. In MIN6-Con cells, glucose inhibits the KATP channel, leading to Ca2+ influx and transcription of insulin-independent genes, whereas most of the effects on transcription appear to be mediated through the paracrine/autocrine effects on insulin secretion. In this model, we hypothesize also a negative feedback of insulin on the KATP channel. In the functional absence of the insulin receptor (e.g. in IRKD cells), this feedback mechanism is diminished, resulting in enhanced glucose-mediated insulin secretion and gene transcription. The enhanced effects of glucose on Ca2+ flux in IRKD cells are also consistent with this model. Measuring KATP channel activity in the IRKD cells can directly assess the validity of this model.

In conclusion, the results of these studies indicate that insulin receptor signaling has important roles in gene expression and function in mouse insulinoma (MIN6) cells. How insulin signaling contributes to insulin synthesis, proliferation, insulin secretion, and gene expression remains to be further defined. Reduced insulin signaling, as manifested as insulin resistance, in animal models and human diabetes resulted in reduced {beta} cell mass and impaired function. The findings in IRKD cells may suggest potential mechanisms whereby reduced insulin signaling in {beta} cells may contribute to these processes.


   FOOTNOTES
 
* This work was supported in part by American Diabetes Association Mentor-based Fellowship (to M. O.), Canadian Institutes of Health Research Senior Fellowship (to J. D. J.), National Institutes of Health Grants DK16746, DK56954, and DK99007 (to M. A. P.), and the Washington University Diabetes Research and Training Center. Back

{boxs} The on-line version of this article (available at http://www.jbc.org) contains Supplemental Tables 1S and 2S. Back

{ddagger} To whom correspondence should be addressed: Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, 660 S. Euclid Ave., Campus Box 8127, St. Louis, MO 63110. Tel.: 314-362-8680; Fax: 314-747-2692; E-mail: apermutt{at}im.wustl.edu.

1 The abbreviations used are: IR, insulin receptor; {beta}IRKO, {beta} cell-specific insulin receptor knock-out; siRNA, small interfering RNA; FBS, fetal calf serum; IRKD, insulin receptor knockdown; RT, reverse transcription; qRT, quantitative RT; CI, confidence intervals; BrdUrd, bromodeoxyuridine; FITC, fluorescein isothiocyanate; PBS, phosphate-buffered saline; TUNEL, terminal deoxynucleotidyltransferase-mediated dUTP nick end labeling; PI3-kinase, phosphatidylinositol 3-kinase; ERK, extracellular signal-regulated kinase; IRS, insulin receptor substrate. Back


   ACKNOWLEDGMENTS
 
We gratefully acknowledge the D. Melton laboratory (Harvard University) and the laboratories of K. Kaestner and C. Stoeckert (University of Pennsylvania) as well as Ellen Ostlund, Sandy Clifton, Hiroshi Inoue, Chris Sawyer, Mike Heinz, Wesley Warren, Elaine Mardis, and other members of the Genome Sequencing Center for their work with EPCon and with microarrays. We also thank Gary Stormo and Burton Wice for helpful suggestions and Jessica Murray and Sara Martinez for technical assistance. We thank Stanley Misler for the use of his imaging setup.



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